publications

publications by categories in reversed chronological order.

See my full publication list in google scholar.

2024

  1. ICML 24
    Constrained Reinforcement Learning Under Model Mismatch
    Zhongchang Sun, Sihong He, Fei Miao, and 1 more author
    arXiv preprint arXiv:2405.01327, 2024
  2. ICML 24
    Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments
    Han Wang, Sihong He, Zhili Zhang, and 2 more authors
    arXiv preprint arXiv:2405.19499, 2024
  3. Adaptive Uncertainty Quantification for Trajectory Prediction Under Distributional Shift
    Huiqun Huang, Sihong He, and Fei Miao
    arXiv preprint arXiv:2406.12100, 2024
  4. What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
    Songyang Han, Sanbao Su, Sihong He, and 4 more authors
    Transactions on Machine Learning Research (TMLR), 2024

2023

  1. A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in AMoD Systems
    Sihong He, Yue Wang, Shuo Han, and 2 more authors
    In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
  2. Robust electric vehicle balancing of autonomous mobility-on-demand system: A multi-agent reinforcement learning approach
    Sihong He, Shuo Han, and Fei Miao
    In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
  3. Robust Multi-Agent Reinforcement Learning with State Uncertainty
    Sihong He, Songyang Han, Sanbao Su, and 3 more authors
    Transactions on Machine Learning Research (TMLR), 2023
  4. Data-Driven Distributionally Robust Electric Vehicle Balancing for Autonomous Mobility-on-Demand Systems Under Demand and Supply Uncertainties
    Sihong He, Zhili Zhang, Shuo Han, and 5 more authors
    IEEE Transactions on Intelligent Transportation Systems, 2023
  5. Robust Multi-Agent Reinforcement Learning Considering State Uncertainties
    Sihong He, Songyang Han, Sanbao Su, and 3 more authors
    AI4ABM Workshop at the International Conference on Learning Representations (ICLR), 2023
  6. A Robust and Constrained Multi-Agent Reinforcement Learning Method for Electric Vehicle Rebalancing in AMoD Systems
    Sihong He, Yue Wang, Shuo Han, and 2 more authors
    AI4ABM Workshop at the International Conference on Learning Representations (ICLR), 2023
  7. Uncertainty quantification of collaborative detection for self-driving
    Sanbao Su, Yiming Li, Sihong He, and 4 more authors
    IEEE International Conference on Robotics and Automation (ICRA), 2023

2022

  1. What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
    Songyang Han, Sanbao Su, Sihong He, and 3 more authors
    In ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2022

2021

  1. Data-driven distributionally robust optimization for vehicle balancing of mobility-on-demand systems
    Fei Miao, Sihong He, Lynn Pepin, and 5 more authors
    ACM Transactions on Cyber-Physical Systems, 2021

2020

  1. Data-driven distributionally robust electric vehicle balancing for mobility-on-demand systems under demand and supply uncertainties
    Sihong He, Lynn Pepin, Guang Wang, and 2 more authors
    In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020